For the construction of the SVD using stochasticity, a method we refer in this
manuscript as stochastic SVD is available [1]} which can be
broken in two stages. First, the construction of a subspace with reduced
dimension in which to represent the input data in an approximate manner; a
matrix is bult in which the columns form a reduced orthonormal basis for the data.
Second, the projection of the observations onto that subspace and the subsequent
computation of the SVD. Both stages are outlined in
Algorithm REF .
